print.summary.grpreg: Summarize a fitted 'grpreg' object

In grpss: Group Screening and Selection

Description

Summarizes a fitted penalized regression model with 'grpreg' class.

Usage

## S3 method for class 'summary.grpreg'
print(x, digits = 4, ...)

Arguments

x	A "summary.grpreg" object.
digits	Number of digits past the decimal point to print out. The default is 4.
...	Optional arguments passed to other methods.

Details

The default lambda is the one at which we obtain the minimum loss (i.e., negative log-likelihood value), if lambda is not specified.

Value

A list with class "summary.grpreg" containing the following components:

n	Number of observations.
p	Number of screened predictors.
penalty	The penalty applied to the model.
model	The type of model.
family	The link function.
criterion	The screening criterion.
lambda	The default or specified regularization parameter.
beta	The estimates of coefficients at the specified lambda.
iter	The number of iterations at the specified lambda.
df	The estimates of effective number of model parameters at the specified lambda.
call	The function call.

Additional elements are contained for the case in which family = "gaussian":

r.squared	The r.squared.
snr	The signal-to-noise ratio.
scale	The scale parameter estimate.

and following elements for the case in which family = "poisson" or "binomial":

logLik	The negative log-likelihood values for the fitted model.
aic	Akaike's information criterion (AIC).
bic	Bayesian information criterion (BIC).
aicc	The AIC with a correction for finite sample sizes (AICC).
pe	The prediction error for family = "binomial".

Author(s)

Debin Qiu, Jeongyoun Ahn

See Also

summary.cv.grpreg

grpss documentation built on May 1, 2019, 7:49 p.m.